Employee attrition is a major challenge for organizations as it impacts productivity, recruitment costs, and workforce stability. This project analyzes employee data to identify key factors influencing attrition and builds predictive models to forecast employee turnover.
- Analyze employee workforce data
- Identify factors contributing to attrition
- Build predictive models using machine learning
- Provide HR insights for retention strategies
- Python
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Scikit-learn
- Google Colab
- Logistic Regression
- Random Forest Classifier
- Lower salary employees have higher attrition probability.
- Work-life balance significantly influences employee retention.
- Early-tenure employees show higher turnover risk.